CN113396587A

CN113396587A - Image component prediction method, device and computer storage medium

Info

Publication number: CN113396587A
Application number: CN201980091266.2A
Authority: CN
Inventors: 霍俊彦; 马彦卓; 万帅; 杨付正; 李新伟; 冉启宏
Original assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd
Current assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd
Priority date: 2019-06-25
Filing date: 2019-06-25
Publication date: 2021-09-14
Also published as: EP3952308A4; US11363257B2; EP3952308A1; CN113840142B; US11973936B2; US20220248001A1; PL3952308T3; CN113840142A; KR20220024214A; US20240244186A1; CN116962677A; EP4336839A2; ES2975857T3; JP2022541115A; WO2020258016A1; EP4336839A3; EP3952308B1; US20220053182A1; JP7448568B2; CN116866560A

Abstract

An image component prediction method, apparatus, and computer storage medium. The method comprises the following steps: acquiring a first reference pixel set corresponding to a component of a to-be-predicted image of a coding block in a video image (S501); when the number of effective pixels in the first reference pixel set is smaller than a preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component (S502); when the number of effective pixels in the first reference pixel set is greater than or equal to a preset number, screening the first reference pixel set to obtain a second reference pixel set (S503); when the number of effective pixel points in the second reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the image component to be predicted (S504); when the number of effective pixel points in the second reference pixel set is equal to the preset number, determining a model parameter through the second reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameter; wherein, the prediction model is used for implementing the prediction processing on the image component to be predicted so as to obtain a prediction value corresponding to the image component to be predicted (S505).

Description

Image component prediction method, device and computer storage medium

Technical Field

The embodiment of the application relates to the technical field of video coding and decoding, in particular to an image component prediction method, an image component prediction device and a computer storage medium.

Background

With the improvement of the requirement of people on the video display quality, new video application forms such as high-definition videos and ultrahigh-definition videos are produced. h.265/High Efficiency Video Coding (HEVC) has failed to meet the demand for rapid development of Video applications, and Joint Video research Team (Joint Video expansion Team, jmet) has proposed the next generation Video Coding standard h.266/multifunctional Video Coding (VVC), and its corresponding Test Model is a VVC reference software Test Model (VVC Test Model, VTM).

In VTM, an image component prediction method based on a prediction model by which a chrominance component can be predicted from a luminance component of a current Coding Block (CB) has been integrated. However, when the prediction model is constructed, because the number of adjacent reference pixels used for model parameter derivation is different, not only is additional processing added, but also the computational complexity is increased.

Disclosure of Invention

The embodiment of the application provides an image component prediction method, an image component prediction device and a computer storage medium, on the premise of not changing the coding and decoding prediction performance, the derivation process of model parameters is unified, and meanwhile, aiming at the condition that the number of effective pixel points in an adjacent reference pixel set is smaller than the preset number, no additional processing module is added, so that no additional processing is needed, and the calculation complexity is reduced.

The technical scheme of the embodiment of the application can be realized as follows:

in a first aspect, an embodiment of the present application provides an image component prediction method, where the method includes:

acquiring a first reference pixel set corresponding to a component of a to-be-predicted image of a coding block in a video image;

when the number of effective pixel points in the first reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component;

when the number of effective pixel points in the first reference pixel set is greater than or equal to a preset number, screening the first reference pixel set to obtain a second reference pixel set; the number of effective pixel points in the second reference pixel set is less than or equal to a preset number;

when the number of effective pixel points in the second reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component;

when the number of effective pixel points in the second reference pixel set is equal to the preset number, determining a model parameter through the second reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameter; the prediction model is used for realizing the prediction processing of the image component to be predicted so as to obtain a prediction value corresponding to the image component to be predicted.

In a second aspect, an embodiment of the present application provides an image component prediction apparatus, including: an acquisition unit, a prediction unit, and a screening unit, wherein,

the acquiring unit is configured to acquire a first reference pixel set corresponding to a to-be-predicted image component of a coding block in a video image;

the prediction unit is configured to, when the number of effective pixels in the first reference pixel set is smaller than a preset number, use a preset component value as a prediction value corresponding to the to-be-predicted image component;

the screening unit is configured to screen the first reference pixel set to obtain a second reference pixel set when the number of effective pixels in the first reference pixel set is greater than or equal to a preset number; the number of effective pixel points in the second reference pixel set is less than or equal to a preset number;

the prediction unit is further configured to, when the number of effective pixels in the second reference pixel set is smaller than a preset number, use a preset component value as a prediction value corresponding to the to-be-predicted image component; when the number of effective pixel points in the second reference pixel set is equal to the preset number, determining a model parameter through the second reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameter; the prediction model is used for realizing the prediction processing of the image component to be predicted so as to obtain a prediction value corresponding to the image component to be predicted.

In a third aspect, an embodiment of the present application provides an image component prediction apparatus, including: a memory and a processor;

the memory for storing a computer program operable on the processor;

the processor, when executing the computer program, is adapted to perform the method as described in the first aspect.

In a fourth aspect, embodiments of the present application provide a computer storage medium storing an image component prediction program that, when executed by at least one processor, implements the method as described in the first aspect.

The embodiment of the application provides an image component prediction method, an image component prediction device and a computer storage medium, wherein a first reference pixel set corresponding to a to-be-predicted image component of a coding block in a video image is obtained; when the number of effective pixel points in the first reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the image component to be predicted; when the number of effective pixel points in the first reference pixel set is larger than or equal to the preset number, screening the first reference pixel set to obtain a second reference pixel set, wherein the number of effective pixel points in the second reference pixel set is smaller than or equal to the preset number; when the number of effective pixel points in the second reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the image component to be predicted; when the number of effective pixel points in the second reference pixel set is equal to the preset number, determining a model parameter through the second reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameter, wherein the prediction model is used for realizing prediction processing of the image component to be predicted so as to obtain a prediction value corresponding to the image component to be predicted; in this way, when the number of effective pixels in the first reference pixel set is smaller than the preset number or the number of effective pixels in the second reference pixel set is smaller than the preset number, the preset default value is directly adopted as the predicted value corresponding to the image component to be predicted; only when the number of effective pixel points in the second reference pixel set meets the preset number, determining model parameters according to the first reference pixel set to establish a prediction model of the image component to be predicted, so that the derivation process of the model parameters is unified; in addition, for the condition that the number of effective pixels in the first reference pixel set or the second reference pixel set is smaller than the preset number, especially for the condition that the number of effective pixels is 0 or 2, because no additional processing module is added, the preset default value is directly adopted as the predicted value corresponding to the image component to be predicted, so that no additional processing is needed, and the calculation complexity is reduced.

Drawings

Fig. 1 is a schematic distribution diagram of effective neighboring areas according to an embodiment of the present disclosure;

fig. 2 is a schematic distribution diagram of a selection area in three modes according to an embodiment of the present disclosure;

fig. 3 is a block diagram illustrating a video coding system according to an embodiment of the present disclosure;

fig. 4 is a block diagram illustrating a video decoding system according to an embodiment of the present application;

fig. 5 is a schematic flowchart of an image component prediction method according to an embodiment of the present disclosure;

fig. 6A is a schematic structural diagram illustrating selection of adjacent reference pixels in INTRA _ LT _ CCLM mode according to an embodiment of the present disclosure;

fig. 6B is a schematic structural diagram of selecting an adjacent reference pixel in INTRA _ L _ CCLM mode according to an embodiment of the present disclosure;

fig. 6C is a schematic structural diagram illustrating selection of adjacent reference pixels in INTRA _ T _ CCLM mode according to an embodiment of the present application;

fig. 7 is a schematic flowchart of another image component prediction method according to an embodiment of the present application;

fig. 8A is a schematic structural diagram of 0 effective pixels generated in an INTRA _ LT _ CCLM mode according to an embodiment of the present disclosure;

fig. 8B is a schematic structural diagram of 0 effective pixels generated in an INTRA _ L _ CCLM mode according to an embodiment of the present disclosure;

fig. 8C is a schematic structural diagram of generating 0 effective pixels in an INTRA _ T _ CCLM mode according to an embodiment of the present disclosure;

fig. 9A is a schematic structural diagram of generating 2 effective pixels in an INTRA _ LT _ CCLM mode according to an embodiment of the present disclosure;

fig. 9B is a schematic structural diagram of generating 2 effective pixels in an INTRA _ L _ CCLM mode according to an embodiment of the present disclosure;

fig. 9C is a schematic structural diagram of generating 2 effective pixels in an INTRA _ T _ CCLM mode according to an embodiment of the present disclosure;

FIG. 10 is a schematic flow chart illustrating model parameter derivation according to an embodiment of the present disclosure;

FIG. 11 is a simplified flowchart of model parameter derivation according to an embodiment of the present disclosure;

FIG. 12 is a simplified flow chart of another model parameter derivation provided in embodiments of the present application;

fig. 13 is a schematic structural diagram illustrating an image component prediction apparatus according to an embodiment of the present disclosure;

fig. 14 is a schematic diagram illustrating a specific hardware structure of an image component prediction apparatus according to an embodiment of the present disclosure;

fig. 15 is a schematic structural diagram of an encoder according to an embodiment of the present disclosure;

fig. 16 is a schematic structural diagram of a decoder according to an embodiment of the present application.

Detailed Description

So that the manner in which the features and elements of the present embodiments can be understood in detail, a more particular description of the embodiments, briefly summarized above, may be had by reference to embodiments, some of which are illustrated in the appended drawings.

In a video image, a first image component, a second image component and a third image component are generally adopted to characterize a coding block; wherein the three image components are respectively a luminance component, a blue chrominance component and a red chrominance component, and specifically, the luminance component is generally represented by a symbol Y, the blue chrominance component is generally represented by a symbol Cb or U, and the red chrominance component is generally represented by a symbol Cr or V; thus, the video image can be represented in YCbCr format, and also in YUV format.

In the embodiment of the present application, the first image component may be a luminance component, the second image component may be a blue chrominance component, and the third image component may be a red chrominance component, but the embodiment of the present application is not particularly limited.

In the current video image or video encoding and decoding process, the Cross-component Prediction technology mainly includes a Cross-component Linear Model Prediction (CCLM) mode and a Multi-Directional Linear Model Prediction (MDLM) mode, and the corresponding Prediction Model can realize the Prediction between image components such as a first image component to a second image component, a second image component to a first image component, a first image component to a third image component, a third image component to a first image component, a second image component to a third image component, or a third image component to a second image component, no matter the Model parameter derived according to the CCLM mode or the Model parameter derived according to the MDLM mode.

Taking the prediction of a first picture component to a second picture component as an example, in order to reduce redundancy between the first picture component and the second picture component, the CCLM mode is used in VVC, when the first picture component and the second picture component are of the same coding block, i.e. a prediction value for the second picture component is constructed from the first picture component reconstruction value of the same coding block, as shown in equation (1),

Pred _C[i,j]＝α·Rec _L[i,j]+β (1)

wherein, i, j represents the position coordinate of the pixel point in the coding block, i represents the horizontal direction, j represents the vertical direction, Pred_C[i,j]Representing the position coordinates in the code block as [ i, j ]]Corresponding to the pixel point of (2) a second image component prediction value, Pred_L[i,j]Representing the (down-sampled) position coordinates in the same block as [ i, j ]]The corresponding first image component reconstruction values of pixel points of (a) and (b) represent model parameters.

For a coding block, its neighboring regions may include a left neighboring region, an upper neighboring region, a lower left neighboring region, and an upper right neighboring region. In VVC, three cross-component linear model prediction modes may be included, respectively: left and upper adjacent INTRA CCLM modes (which may be represented by INTRA _ LT _ CCLM modes), left and lower left adjacent INTRA CCLM modes (which may be represented by INTRA _ L _ CCLM modes), and upper right adjacent INTRA CCLM modes (which may be represented by INTRA _ T _ CCLM modes). In the three modes, a preset number (for example, 4) of adjacent reference pixels can be selected for deriving the model parameters α and β in each mode, and the three modes are the most different in that the selection regions corresponding to the adjacent reference pixels for deriving the model parameters α and β are different.

Specifically, for a coding block size corresponding to the second image component is W × H, assuming that an upper side selection region corresponding to an adjacent reference pixel point is W ', and a left side selection region corresponding to the adjacent reference pixel point is H'; in this way it is possible to obtain,

for the INTRA _ LT _ CCLM mode, adjacent reference pixels can be selected from an upper adjacent region and a left adjacent region, that is, W ═ W, H ═ H;

for the INTRA _ L _ CCLM mode, the adjacent reference pixel points may be selected from the left adjacent area and the left lower adjacent area, that is, H ═ W + H, and W ═ 0 is set;

for INTRA _ T _ CCLM mode, the adjacent reference pixel point may be selected from the upper adjacent region and the upper right adjacent region, that is, W ═ W + H, and set H ═ 0.

It should be noted that, in the VVC latest reference software VTM5.0, for the upper right adjacent region, at most, pixels in the W range are stored, and for the lower left adjacent region, at most, pixels in the H range are stored; therefore, although the range of the selection regions of the INTRA _ L _ CCLM mode and the INTRA _ T _ CCLM mode is defined as W + H, in practical applications, the selection region of the INTRA _ L _ CCLM mode will be limited to H + H, and the selection region of the INTRA _ T _ CCLM mode will be limited to W + W; in this way it is possible to obtain,

for the INTRA _ L _ CCLM mode, adjacent reference pixels can be selected from a left adjacent region and a left lower adjacent region, and H' ═ min { W + H, H + H };

for INTRA _ T _ CCLM mode, the neighboring reference pixel may be selected from the upper neighboring region and the upper right neighboring region, W ═ min { W + H, W + W }.

Referring to fig. 1, a schematic distribution diagram of an effective neighboring area provided by an embodiment of the present application is shown. In fig. 1, the left side adjacent region, the lower left side adjacent region, the upper side adjacent region, and the upper right side adjacent region are all effective. On the basis of fig. 1, the selection regions for the three modes are shown in fig. 2. In fig. 2, (a) shows a selection region of the INTRA _ LT _ CCLM mode, including a left adjacent region and an upper adjacent region; (b) a selection region of the INTRA _ L _ CCLM mode is shown, which comprises a left adjacent region and a lower left adjacent region; (c) the selection region of INTRA _ T _ CCLM mode is shown, including the upper neighboring region and the upper right neighboring region. Thus, after the selection areas of the three modes are determined, the selection of the reference points for model parameter derivation can be performed within the selection areas. The reference points selected in this way can be called as adjacent reference pixel points, and usually the number of the adjacent reference pixel points is at most 4; and for a W × H coding block with a certain size, the positions of the adjacent reference pixels are generally determined.

However, for some special cases, such as the boundary condition of the coding block, the unpredictable condition, and the condition that the coding sequence leads to the inability to obtain the adjacent reference pixels, even the coding block division is performed according to tile partitions (tiles) and slices (slices), the adjacent area may have the possibility of being invalid, so that the number of the adjacent reference pixels selected from the adjacent area is less than 4, that is, only 0 or 2 adjacent reference pixels may be selected; the number of adjacent reference pixels used for model parameter derivation is not uniform, so that additional 'copying' operation is added, and meanwhile, the calculation complexity is improved.

On the premise of not changing the encoding and decoding predictive performance, in order to unify the derivation process of model parameters and reduce the computational complexity, the embodiment of the application provides an image component prediction method, which comprises the steps of acquiring a first reference pixel set corresponding to a to-be-predicted image component of a coding block in a video image; when the number of effective pixel points in the first reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the image component to be predicted; when the number of effective pixel points in a first reference pixel set is larger than or equal to a preset number, screening the first reference pixel set to obtain a second reference pixel set, wherein the number of effective pixel points in the second reference pixel set is smaller than or equal to the preset number; when the number of effective pixel points in the second reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the image component to be predicted; when the number of effective pixel points in the second reference pixel set is equal to the preset number, determining model parameters through the first reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameters; the prediction model is used for realizing the prediction processing of the image component to be predicted so as to obtain a prediction value corresponding to the image component to be predicted; in this way, the CCLM mode is forbidden under the condition that the number of effective pixels in the first reference pixel set is less than the preset number or the number of effective pixels in the second reference pixel set is less than the preset number, and the preset default value is directly adopted as the predicted value corresponding to the image component to be predicted; in addition, the derivation of the model parameters is executed only when the number of the effective pixels in the second reference pixel set is the preset number, that is, the CCLM mode is executed, so that the derivation process of the model parameters is also unified.

Embodiments of the present application will be described in detail below with reference to the accompanying drawings.

Referring to fig. 3, a block diagram of an example of a video coding system provided in an embodiment of the present application is shown; as shown in fig. 3, the video Coding system 300 includes a transform and quantization unit 301, an intra estimation unit 302, an intra prediction unit 303, a motion compensation unit 304, a motion estimation unit 305, an inverse transform and inverse quantization unit 306, a filter control analysis unit 307, a filtering unit 308, an encoding unit 309, a decoded image buffer unit 310, and the like, wherein the filtering unit 308 may implement deblocking filtering and Sample Adaptive 0 offset (SAO) filtering, and the encoding unit 309 may implement header information encoding and Context-based Adaptive Binary arithmetic Coding (CABAC). For an input original video signal, a video Coding block can be obtained by dividing a Coding Tree Unit (CTU), and then residual pixel information obtained by intra-frame or inter-frame prediction is transformed by a transformation and quantization Unit 301, including transforming the residual information from a pixel domain to a transform domain and quantizing the obtained transform coefficient, so as to further reduce the bit rate; the intra estimation unit 302 and the intra prediction unit 303 are used for intra prediction of the video coding block; in particular, intra estimation unit 302 and intra prediction unit 303 are used to determine the intra prediction mode to be used to encode the video coding block; motion compensation unit 304 and motion estimation unit 305 are used to perform inter-prediction encoding of a received video coding block relative to one or more blocks in one or more reference frames to provide temporal prediction information; motion estimation performed by the motion estimation unit 305 is a process of generating motion vectors that can estimate the motion of the video coding block, and then motion compensation is performed by the motion compensation unit 304 based on the motion vectors determined by the motion estimation unit 305; after determining the intra prediction mode, the intra prediction unit 303 is also configured to supply the selected intra prediction data to the encoding unit 309, and the motion estimation unit 305 also sends the calculated determined motion vector data to the encoding unit 309; furthermore, the inverse transform and inverse quantization unit 306 is used for reconstruction of the video coding block, reconstructing a residual block in the pixel domain, the reconstructed residual block removing blocking artifacts through the filter control analysis unit 307 and the filtering unit 308, and then adding the reconstructed residual block to a predictive block in the frame of the decoded picture buffer unit 310 to generate a reconstructed video coding block; the encoding unit 309 is configured to encode various encoding parameters and quantized transform coefficients, and in a CABAC-based encoding algorithm, context content may be based on adjacent encoding blocks, may be configured to encode information indicating the determined intra prediction mode, and output a code stream of the video signal; the decoded picture buffer unit 310 is used to store reconstructed video coding blocks for prediction reference. As the video coding proceeds, new reconstructed video coding blocks are generated, and these reconstructed video coding blocks are stored in the decoded picture buffer unit 310.

Referring to fig. 4, a block diagram of an example of a video decoding system provided in an embodiment of the present application is shown; as shown in fig. 4, the video decoding system 400 includes a decoding unit 401, an inverse transform and inverse quantization unit 402, an intra prediction unit 403, a motion compensation unit 404, a filtering unit 405, a decoded image buffer unit 406, and the like, wherein the decoding unit 401 can implement header information decoding and CABAC decoding, and the filtering unit 405 can implement deblocking filtering and SAO filtering. After the input video signal is subjected to the encoding process of fig. 2, outputting a code stream of the video signal; the code stream is input into the video decoding system 400, and first passes through the decoding unit 401 to obtain a decoded transform coefficient; processing the transform coefficients by an inverse transform and inverse quantization unit 402 to produce a residual block in the pixel domain; intra-prediction unit 403 may be used to generate prediction data for a current video decoded block based on the determined intra-prediction mode and data from previously decoded blocks of the current frame or picture; motion compensation unit 404 is a predictive block that determines prediction information for a video decoded block by parsing motion vectors and other associated syntax elements and uses the prediction information to generate the video decoded block being decoded; forming a decoded video block by summing the residual block from the inverse transform and inverse quantization unit 402 with the corresponding predictive block generated by the intra prediction unit 403 or the motion compensation unit 404; the decoded video signal passes through a filtering unit 405 to remove blocking artifacts, which may improve video quality; the decoded video blocks are then stored in the decoded picture buffer unit 406, and the decoded picture buffer unit 406 stores the reference pictures for subsequent intra prediction or motion compensation, and also for the output of the video signal, i.e. the restored original video signal is obtained.

The image component prediction method in the embodiment of the present application is mainly applied to the intra prediction unit 303 shown in fig. 3 and the intra prediction unit 403 shown in fig. 4, and is particularly applied to the CCLM prediction portion in intra prediction. That is to say, the image component prediction method in the embodiment of the present application may be applied to a video coding system, a video decoding system, or even applied to both the video coding system and the video decoding system, but the embodiment of the present application is not limited in particular. When the method is applied to the intra prediction unit 303 part, the "coding block in video image" specifically refers to the current coding block in intra prediction; when the method is applied to the intra prediction unit 403 portion, the "encoded block in video image" specifically refers to the currently decoded block in intra prediction.

Based on the application scenario example of fig. 3 or fig. 4, referring to fig. 5, a flowchart of an image component prediction method provided in an embodiment of the present application is shown. As shown in fig. 5, the method may include:

s501: acquiring a first reference pixel set corresponding to a component of a to-be-predicted image of a coding block in a video image;

it should be noted that a video image may be divided into a plurality of coding blocks, each coding block may include a first image component, a second image component, and a third image component, and the coding block in the embodiment of the present application is a current block to be subjected to an encoding process in the video image. When the first image component needs to be predicted through the prediction model, the image component to be predicted is the first image component; when the second image component needs to be predicted through the prediction model, the image component to be predicted is the second image component; and when the third image component needs to be predicted through the prediction model, the image component to be predicted is the third image component.

It should be further noted that, when the left neighboring area, the lower left neighboring area, the upper neighboring area, and the upper right neighboring area are all valid areas, for the INTRA _ LT _ CCLM mode, the first reference pixel set is composed of neighboring reference pixels in the left neighboring area and the upper neighboring area of the coding block, as shown in (a) of fig. 2; for INTRA _ L _ CCLM mode, the first reference pixel set is composed of neighboring reference pixels in the left neighboring region and the left lower neighboring region of the coding block, as shown in fig. 2 (b); for INTRA _ T _ CCLM mode, the first set of reference pixels is composed of neighboring reference pixels in the upper neighboring region and the upper right neighboring region of the coding block, as shown in fig. 2 (c).

In some embodiments, optionally, for S501, the obtaining a first reference pixel set corresponding to an image component to be predicted of an encoded block in a video image may include:

s501 a-1: acquiring a reference pixel point adjacent to at least one edge of the coding block; wherein the at least one edge comprises a left side of the coding block and/or an upper side of the coding block;

s501 a-2: and forming a first reference pixel set corresponding to the image component to be predicted based on the reference pixel points.

It should be noted that at least one edge of the coding block may include a left side edge of the coding block and/or an upper side edge of the coding block; that is, at least one edge of the coding block may refer to an upper side of the coding block, may also refer to a left side of the coding block, and may even refer to an upper side and a left side of the coding block, which is not specifically limited in the embodiment of the present application.

Thus, for the INTRA _ LT _ CCLM mode, when all of the left side adjacent region and the upper side adjacent region are valid regions, the first reference pixel set may be composed of reference pixel points adjacent to the left side of the coding block and reference pixel points adjacent to the upper side of the coding block, and when the left side adjacent region is a valid region and the upper side adjacent region is an invalid region, the first reference pixel set may be composed of reference pixel points adjacent to the left side of the coding block; when the left adjacent area is an invalid area and the upper adjacent area is an effective area, the first reference pixel set may be composed of reference pixels adjacent to the upper side of the coding block.

In some embodiments, optionally, for S501, the obtaining a first reference pixel set corresponding to a to-be-predicted image component of a coded block in a video image may include:

s501 b-1: acquiring reference pixel points in reference rows or reference columns adjacent to the coding blocks; wherein the reference row is composed of rows adjacent to the upper side and the upper right side of the coding block, and the reference column is composed of columns adjacent to the left side and the lower left side of the coding block;

s501 b-2: and forming a first reference pixel set corresponding to the image component to be predicted based on the reference pixel points.

It should be noted that, the reference row adjacent to the coding block may be composed of rows adjacent to the upper side and the upper right side of the coding block, and the reference column adjacent to the coding block may be composed of columns adjacent to the left side and the lower left side of the coding block; the reference row or reference column adjacent to the coding block may refer to a reference row adjacent to an upper side of the coding block, may also refer to a reference column adjacent to a left side of the coding block, and may even refer to a reference row or reference column adjacent to other sides of the coding block, which is not specifically limited in the embodiments of the present application. For convenience of description, in the embodiments of the present application, reference rows in which coding blocks are adjacent will be described as an example of the above reference rows in which sides are adjacent, and reference columns in which coding blocks are adjacent will be described as an example of the reference columns in which sides are adjacent.

The reference pixels in the reference row adjacent to the coding block may include reference pixels adjacent to the upper side and the upper right side (also referred to as adjacent reference pixels corresponding to the upper side and the upper right side), where the upper side represents the upper side of the coding block, and the upper right side represents a length of a side of the coding block, which is horizontally extended to the right and has the same height as the current coding block; the reference pixels in the reference column adjacent to the coding block may further include reference pixels adjacent to the left side and the lower left side (also referred to as adjacent reference pixels corresponding to the left side and the lower left side), where the left side represents the left side of the coding block, and the lower left side represents a side length of the coding block, which is vertically extended downward from the left side of the coding block and has the same width as the current decoding block; however, the embodiments of the present application are not particularly limited.

Thus, for the INTRA _ L _ CCLM mode, when the left adjacent region and the left lower adjacent region are valid regions, the first reference pixel set may be composed of reference pixels in a reference column adjacent to the coding block at this time; for INTRA _ T _ CCLM mode, when the upper neighboring region and the upper right neighboring region are valid regions, the first reference pixel set at this time may be composed of reference pixels in a reference row adjacent to the coding block.

S502: when the number of effective pixel points in the first reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component;

it should be noted that the number of effective pixels may be determined according to the effectiveness of the adjacent region, or may be determined according to the number of effective pixels in the selected region. Aiming at some special conditions, such as the boundary condition of a coding block, the unpredictable condition and the condition that the coding sequence causes that adjacent reference pixels cannot be obtained, even the coding block is divided according to tile and slice, at this time, a left adjacent region, a left lower adjacent region, an upper adjacent region and a right upper adjacent region are not all effective regions, and the condition of an invalid region may exist, so that the number of effective pixels in a selected region is smaller than the preset number, and the number of effective pixels in a first reference pixel set is smaller than the preset number.

It should be further noted that the preset number is a preset judgment value of the number of effective pixels, and is used for measuring whether model parameter derivation is executed on the to-be-predicted image component and constructing a prediction model; the preset number may be 4, but the embodiment of the present application is not particularly limited. In this way, assuming that the preset number is4, that is, when the number of effective pixels in the first reference pixel set is 0 or 2, the preset component value can be directly used as the predicted value corresponding to the to-be-predicted image component, so as to reduce the computational complexity.

In addition, the preset component value is used to indicate a fixed value (may also be referred to as a default value) corresponding to a preset image component to be predicted. Wherein the predetermined component value is mainly related to bit information of the current video image. Therefore, in some embodiments, for S502, when the number of effective pixels in the first reference pixel set is less than a preset number, the taking a preset component value as a predicted value corresponding to the to-be-predicted image component may include:

s502 a: determining a preset component range corresponding to the image component to be predicted based on bit information of a video image;

s502 b: determining a middle value of the preset component range according to the preset component range, and taking the middle value as a predicted value corresponding to the image component to be predicted; wherein the intermediate value is represented as a preset component value.

It should be noted that, in the embodiment of the present application, an intermediate value of a preset component range corresponding to a to-be-predicted image component may be used as a preset component value, and then the intermediate value may be used as a predicted value corresponding to the to-be-predicted image component. Wherein, the bit depth of the image component to be predicted is represented by BitDepthC, and the calculation mode for obtaining the intermediate value of the image component to be predicted is 1< < (BitDepthC-1); the calculation method may be specifically set according to actual conditions, and the embodiment of the present application is not particularly limited.

Exemplarily, the image component to be predicted takes a chroma component as an example, and assuming that the current video image is an 8-bit video, the component range corresponding to the chroma component is 0-255, the intermediate value is 128 at this time, and the preset component value may be 128 at this time, that is, the default value is 128; assuming that the current video image is a 10-bit video, the range of the components corresponding to the chrominance components is 0 to 1023, the intermediate value is 512, and the default value is 512, where the predetermined component value can be 512. In the embodiment of the present application, the bit information of the video image will be exemplified by 10 bits, that is, the predetermined component value is 512.

Further, in some embodiments, for S502, after taking a preset component value as a predicted value corresponding to the to-be-predicted image component, the method may further include:

s502 c: and aiming at each pixel point in the coding block, filling a predicted value of the component of the image to be predicted of each pixel point by using the preset component value.

It should be noted that, in the case that the number of effective pixels in the first reference pixel set is smaller than the preset number, the prediction value of the to-be-predicted image component in the coding block is directly filled by using a fixed default value without adding an additional processing module.

Exemplarily, assuming that the preset component value is 512 and the to-be-predicted image component is a chroma component, the chroma prediction value corresponding to each pixel point in the coding block may be directly filled with 512.

S503: when the number of effective pixel points in the first reference pixel set is greater than or equal to a preset number, screening the first reference pixel set to obtain a second reference pixel set;

it should be noted that, in the first parameter pixel set, some unimportant reference pixels (for example, the correlation of the reference pixels is poor) or some abnormal reference pixels may exist, and in order to ensure the accuracy of the prediction model, the reference pixels need to be removed, so as to obtain a second reference pixel set, where the number of effective pixels in the second reference pixel set is less than or equal to the preset number. In practical application, the number of effective pixels included in the second reference pixel set is usually 4, but the embodiment of the present application is not particularly limited.

It should be further noted that when the number of effective pixels in the first reference pixel set is greater than or equal to the preset number, the first reference pixel set may be further filtered to obtain a second reference pixel set; after the second reference pixel set is obtained, the judgment still needs to be carried out according to the number of the effective pixel points in the second reference pixel set and the preset number; if the number of effective pixel points in the second reference pixel set is less than the preset number, the preset component value can be used as a predicted value corresponding to the image component to be predicted; if the number of the effective pixel points in the second reference pixel set is equal to the preset number, the model parameters can be deduced according to the second reference pixel set.

Further, in some embodiments, for S503, the screening the first reference pixel set to obtain a second reference pixel set may include:

determining the position of a pixel point to be selected based on the pixel position and/or the image component intensity corresponding to each adjacent reference pixel point in the first reference pixel set;

selecting effective pixel points corresponding to the pixel points to be selected from the first reference pixel set according to the determined pixel points to be selected, and forming the selected effective pixel points into a second reference pixel set; and the number of effective pixel points in the second reference pixel set is less than or equal to a preset number.

Specifically, the screening of the first reference pixel set may be performed according to the positions of the reference pixels to be selected, or may be performed according to the intensity (such as luminance value, chrominance value, etc.) of the image components, so that the screened reference pixels to be selected form a second reference pixel set. The following description will be given taking the reference pixel point position to be selected as an example.

Assuming that the number of effective pixel samples in the upper side area and the upper right side area adjacent to the current coding block is numSampT, and the number of effective pixel samples in the left side area and the lower left side area adjacent to the current coding block is numSampL, the screening process is as follows (where avail t represents the effectiveness of adjacent rows on the current coding block, avail l represents the effectiveness of left adjacent columns of the current coding block, nTbW represents the width of the current coding block, and nTbH represents the height of the current coding block):

if the INTRA prediction mode of the current block is the INTRA _ LT _ CCLM mode,

numSampT＝availTnTbW:0

numSampL＝availLnTbH:0

if not, then,

numSampT＝(availT&&predModeIntra＝＝INTRA_T_CCLM)？(nTbW+

Min(numTopRight,nTbH)):0

numSampL＝(availL&&predModeIntra＝＝INTRA_L_CCLM)？(nTbH+

Min(numLeftBelow,nTbW)):0

here, numTopRight indicates the number of effective pixels in the upper right nTbW range, and numLeftBelow indicates the number of effective pixels in the lower left nTbH range. The number of the screened pixel points on each edge is expressed by cntN, the starting point position is expressed by startPosN, the point selection interval is expressed by pickStepN and the pixel point position to be selected is expressed by pickPosN [ pos ], the derivation process is as follows,

the variable numIs4N indicates whether to screen pixel points on one side only:

numIs4N＝((availT&&availL&&predModeIntra＝＝INTRA_LT_CCLM)？0:1)

the variable startPosN indicates the starting point position:

startPosN＝numSampN>>(2+numIs4N)

the variable pickStepN represents the setpoint interval:

pickStepN＝Max(1,numSampN>>(1+numIs4N))

here, N is replaced by T and L, which can respectively represent the cases of upper-side screening pixel and left-side screening, that is, N side here represents T side or L side. If the validity availN of the N-edge is TRUE and the selected INTRA mode predModeIntra is INTRA _ LT _ CCLM mode or INTRA _ N _ CCLM mode, the number of pixels to be filtered cntN and the pixel position to be selected pickPosN [ pos ] on the N-edge are as follows (note that the total number of pixels to be filtered should be cntT + cntL):

cntN＝Min(numSampN,(1+numIs4N)<<1)

pickPosN[pos]＝(startPosN+pos*pickStepN),with pos＝0...cntN-1

otherwise, the cntN is set to 0, that is, the number of the screened pixel points is 0.

Let us assume that the prediction sample of the current coding block is predSamples x y with x 0.. nTbW-1, y 0.. nTbH-1, which is derived as follows,

if both numSampL and numSampT are invalid, a preset value is set, as shown below,

predSamples[x][y]＝1<<(BitDepth _C-1)，

if not, then,

firstly, acquiring luminance reconstruction samples pY [ x ] [ y ] with x being 0.. nTbW 2-1, y being 0.. nTbH 2-1 of the co-located luminance block;

secondly, acquiring adjacent brightness reconstruction samples pY [ x ] [ y ]:

and a third step of obtaining downsampled luminance reconstruction samples pDSY [ x ] [ y ] with x being 0

Fourthly, when the numSampL is larger than 0, the chroma value pSelC [ idx ] of the left-side selected point is set to p [ -1] [ pickPosL [ idx ] with idx ═ 0.. cntL-1, and the down-sampled reconstructed luma value pSelDsY [ idx ] with idx ═ 0.. cntL-1 of the left-side selected point is obtained.

Fifthly, when numSampT is greater than 0, the chroma value pSelC [ idx ] of the upper side selected point is set to p [ pickPosT [ idx-cntL ] ] [ -1] with idx ═ cntL.. cntL + cnt-1, and the down-sampled reconstructed luma value pSelDsY [ idx ] with idx ═ 0 … cntL + cnt-1 of the upper side selected point is acquired.

Sixth, when cntT + cntL is not equal to 0, the variables minY, maxY, minC and maxC are derived as follows,

when cntT + cntL equals 2, pSelComp [3] is set to pSelComp [0], pSelComp [2] is set to pSelComp [1], pSelComp [0] is set to pSelComp [1], and pSelComp [1] is set to pSelComp [3], where Comp is replaced by DsY and C, respectively, to represent the reconstructed luminance and chrominance of the selected adjacent samples.

The arrays minGrpIdx and maxGrpIdx are derived as follows,

minGrpIdx[0]＝0

minGrpIdx[1]＝2

maxGrpIdx[0]＝1

maxGrpIdx[1]＝3

when pSelDsY [ minGrpIdx [0] ] is greater than pSelDsY [ minGrpIdx [1] ], minGrpIdx [0] and minGrpIdx [1] are exchanged,

(minGrpIdx[0],minGrpIdx[1])＝Swap(minGrpIdx[0],minGrpIdx[1])

when pSelDsY [ maxGrpIdx [0] ] is greater than pSelDsY [ maxGrpIdx [1] ], maxGrpIdx [0] and maxGrpIdx [1] are exchanged,

(maxGrpIdx[0],maxGrpIdx[1])＝Swap(maxGrpIdx[0],maxGrpIdx[1])

when pSelDsY [ minGrpIdx [0] ] is larger than pSelDsY [ maxGrpIdx [1] ], the arrays minGrpIdx and maxGrpIdx are exchanged,

(minGrpIdx,maxGrpIdx)＝Swap(minGrpIdx,maxGrpIdx)

when pSelDsY [ minGrpIdx [1] ] is greater than pSelDsY [ maxGrpIdx [0] ], minGrpIdx [1] and maxGrpIdx [0] are exchanged:

(minGrpIdx[1],maxGrpIdx[0])＝Swap(minGrpIdx[1],maxGrpIdx[0])

the variables maxY, maxC, minY and minC are calculated as follows (representing the mean of the two groups respectively),

maxY＝(pSelDsY[maxGrpIdx[0]]+pSelDsY[maxGrpIdx[1]]+1)>>1

maxC＝(pSelC[maxGrpIdx[0]]+pSelC[maxGrpIdx[1]]+1)>>1

minY＝(pSelDsY[minGrpIdx[0]]+pSelDsY[minGrpIdx[1]]+1)>>1

minC＝(pSelC[minGrpIdx[0]]+pSelC[minGrpIdx[1]]+1)>>1

seventh, linear model parameters a, b, and k are derived as follows (where a is slope (difference in chroma versus difference in luma), b is intercept, k is a shift to a to keep a in integer form),

when numSampL is equal to 0 and numSampT is equal to 0,

k＝0

a＝0

b＝1<<(BitDepth _C-1)

if not, then,

diff＝maxY-minY

if diff is not equal to 0, then,

diffC＝maxC-minC

x＝Floor(Log2(diff))

normDiff＝((diff<<4)>>x)&15

x+＝(normDiff！＝0)？1:0

y＝Floor(Log2(Abs(diffC)))+1

a＝(diffC*(divSigTable[normDiff]|8)+2 ^y-1)>>y

k＝((3+x-y)<1)？1:3+x-y

a＝((3+x-y)<1)？Sign(a)*15:a

b＝minC-((a*minY)>>k)

wherein divSigTable [ ] is, divSigTable [ ] [ {0,7,6,5,5,4,4,3,3,2,2,1,1,1,1,0}

Otherwise (when diff equals 0),

k＝0

a＝0

b＝minC

eighth, chroma prediction samples predSamples [ x ] [ y ] with x being 0.. nTbW-1, y being 0.. nTbH-1 are calculated as follows (where Clip1C limits the prediction value to between 0 and 1023),

predSamples[x][y]＝Clip1C(((pDsY[x][y]*a)>>k)+b)

for example, the screening of 4 adjacent reference pixels is taken as an example for explanation. Assuming that the positions of the reference pixels in the upper selection region W 'are S [0, -1], …, S [ W' -1, -1], the positions of the reference pixels in the left selection region H 'are S < -1,0 >, …, S < -1, H' -1 ]; thus, the screening method for selecting at most 4 adjacent reference pixel points is as follows:

for the INTRA _ LT _ CCLM mode, when an upper adjacent area and a left adjacent area are effective, 2 adjacent reference pixel points to be selected can be screened out in an upper selection area W ', and the corresponding positions of the adjacent reference pixel points are S [ W '/4, -1] and S [3W '/4, -1] respectively; 2 adjacent reference pixel points to be selected can be screened out in the left selection area H ', and the corresponding positions of the adjacent reference pixel points are respectively S < -1 >, H '/4 > and S < -1 >, 3H '/4 >; the 4 adjacent reference pixels to be selected are grouped into a second reference pixel set, as shown in fig. 6A. In fig. 6A, both the left and upper adjacent regions of the coding block are valid, and in order to keep the luminance component and the chrominance component having the same resolution, a downsampling process for the luminance component is also required so that the downsampled luminance component and the chrominance component have the same resolution.

For the INTRA _ L _ CCLM mode, when only the left adjacent area and the lower left adjacent area are valid, 4 adjacent reference pixels to be selected can be screened out in the left selection area H ', and the corresponding positions of the adjacent reference pixels are S < -1 >, H '/8 >, S < -1,3H '/8 >, S < -1,5H '/8 > and S < -1,7H '/8 >, respectively; the 4 adjacent reference pixels to be selected are grouped into a second reference pixel set, as shown in fig. 6B. In fig. 6B, both the left and lower adjacent regions of the coding block are valid, and in order to keep the luminance component and the chrominance component having the same resolution, it is still necessary to perform downsampling processing for the luminance component so that the downsampled luminance component and the chrominance component have the same resolution.

For the INTRA _ T _ CCLM mode, when only the upper adjacent area and the upper right adjacent area are valid, 4 adjacent reference pixels to be selected can be screened out in the upper selection area W ', and the corresponding positions of the adjacent reference pixels are S [ W '/8, -1], S [3W '/8, -1], S [5W '/8, -1] and S [7W '/8, -1], respectively; the 4 adjacent reference pixels to be selected are grouped into a second reference pixel set, as shown in fig. 6C. In fig. 6C, the upper and upper right neighboring areas of the coding block are both valid, and in order to keep the luminance component and the chrominance component having the same resolution, the downsampling process for the luminance component is still required so that the downsampled luminance component and the chrominance component have the same resolution.

In this way, for the condition that the number of effective pixels in the first reference pixel set is greater than or equal to the preset number, a second reference pixel set can be obtained by screening the first reference pixel set, and the second reference pixel set comprises 4 effective pixels;

s504: when the number of effective pixel points in the second reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component;

s505: when the number of effective pixel points in the second reference pixel set is equal to the preset number, determining a model parameter through the second reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameter;

it should be noted that after the first reference pixel set is filtered, a second reference pixel set is obtained. The number of effective pixels in the second reference pixel set may be smaller than a preset number, or may be greater than or equal to the preset number. If the number of the effective pixel points in the second reference pixel set is less than the preset number, directly taking the preset component value as a predicted value corresponding to the image component to be predicted; and if the number of the effective pixel points in the second reference pixel set is greater than or equal to the preset number, determining model parameters through the second reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameters. It should be noted that, because the number of reference pixels used for model parameter derivation is generally 4, the second reference pixel set obtained after the screening is either smaller than the preset number (the second reference pixel set is smaller than 4 effective pixels) or equal to the preset number (the second reference pixel set includes 4 effective pixels).

It should be further noted that the prediction model may be a linear model or a nonlinear model; the nonlinear Model may be a nonlinear form such as a quadratic curve, or a nonlinear form formed by a plurality of linear models, for example, a cross-component prediction technique of a multi-Model CCLM (multi-Model CCLM, MMLM), which is a nonlinear form formed by a plurality of linear models; the embodiments of the present application are not particularly limited. The prediction model can be used for realizing the prediction processing of the image component to be predicted so as to obtain a prediction value corresponding to the image component to be predicted.

After the second reference pixel set is obtained, if the number of effective pixels in the second reference pixel set is equal to the preset number, the model parameter may be determined according to the second reference pixel set. After the model parameters are deduced, a prediction model corresponding to the chromaticity component can be obtained according to the model parameters, as shown in formula (1); and then, the prediction model is used for carrying out prediction processing on the chrominance components so as to obtain a prediction value corresponding to the chrominance components.

Further, in some embodiments, for S505, after obtaining the prediction model corresponding to the image component to be predicted according to the model parameter, the method may further include:

and performing prediction processing on the component of the image to be predicted of each pixel point in the coding block based on the prediction model to obtain a prediction value corresponding to the component of the image to be predicted of each pixel point.

It should be noted that, for the case that the number of effective pixels in the first reference pixel set is greater than or equal to the preset number, at this time, model parameters (such as α and β) need to be determined by the first reference pixel set, and then a prediction model corresponding to a to-be-predicted image component is obtained according to the model parameters, so as to obtain a predicted value corresponding to the to-be-predicted image component of each pixel in the coding block. For example, assuming that the image component to be predicted is a chrominance component, a prediction model corresponding to the chrominance component shown in formula (1) can be obtained according to the model parameters α and β; and then, carrying out prediction processing on the chrominance component of each pixel point in the coding block by using a prediction model shown in the formula (1), so that a predicted value corresponding to the chrominance component of each pixel point can be obtained.

In the embodiment of the application, for the adjacent regions on the left side, the lower left side, the upper side and the upper right side, there may be an effective region or an invalid region, so that the number of effective pixels selected from the adjacent regions may be smaller than the preset number. Therefore, in some embodiments, refer to fig. 7, which shows a schematic flowchart of another image component prediction method provided in the embodiments of the present application. As shown in fig. 7, after S501, the method may further include:

s701: determining the number of effective pixel points in the first reference pixel set, and judging whether the number of the effective pixel points is less than a preset number;

further, after S503, the method may further include:

s702: and judging whether the number of the effective pixel points in the second reference pixel set is less than the preset number.

It should be noted that the determination of the number of effective pixels can be obtained by judging the effectiveness of the adjacent area. Thus, after the number of effective pixels is determined, comparing the number of effective pixels with a preset number, and when the number of effective pixels in the first reference pixel set is smaller than the preset number, executing step S502; when the number of the effective pixel points in the second reference pixel set is less than the preset number, executing step S504; when the number of the effective pixels in the second reference pixel set is greater than or equal to the preset number, step S505 is executed.

It should be noted that the preset number may be 4. The preset number equal to 4 will be described in detail below as an example.

In a possible implementation manner, when the number of effective pixels in the first reference pixel set is greater than or equal to the preset number, since the number of reference pixels used for model parameter derivation is generally 4, at this time, the first reference pixel set may be first screened, so that the number of effective pixels in the first reference pixel set is 4; and then, model parameters are deduced according to the 4 effective pixel points, and a prediction model corresponding to the image component to be predicted is obtained according to the model parameters, so that a prediction value corresponding to the image component to be predicted is obtained.

Specifically, it is assumed that a component to be predicted is a chrominance component, and the chrominance component is predicted from a luminance component. Assume that the numbers of the 4 effective pixels selected by the screening are 0, 1, 2, and 3, respectively. By comparing the 4 selected effective pixel points, based on four comparisons, 2 pixel points with a larger brightness value (which may include a pixel point with a largest brightness value and a pixel point with a second largest brightness value) and 2 pixel points with a smaller brightness value (which may include a pixel point with a smallest brightness value and a pixel point with a second smallest brightness value) can be further selected. Further, two arrays of minIdx 2 and maxIdx 2 can be set to store two groups of pixels, initially, the effective pixels numbered 0 and 2 are placed in minIdx 2, the effective pixels numbered 1 and 3 are placed in maxIdx 2, as shown below,

Init:minIdx[2]＝{0,2},maxIdx[2]＝{1,3}

after that, through four comparisons, 2 pixels with smaller brightness value are stored in minIdx 2, and 2 pixels with larger brightness value are stored in maxIdx 2, as shown in detail below,

Step1:if(L[minIdx[0]]>L[minIdx[1]],swap(minIdx[0],minIdx[1])

Step2:if(L[maxIdx[0]]>L[maxIdx[1]],swap(maxIdx[0],maxIdx[1])

Step3:if(L[minIdx[0]]>L[maxIdx[1]],swap(minIdx,maxIdx)

Step4:if(L[minIdx[1]]>L[maxIdx[0]],swap(minIdx[1],maxIdx[0])

thus, 2 pixel points with smaller brightness values can be obtained, and the corresponding brightness values are respectively used as luma⁰ _minAnd luma¹ _minThe corresponding chromaticity values are respectively indicated by chroma⁰ _minAnd chroma¹ _minRepresents; meanwhile, two pixel points with larger brightness values can be obtained, and the corresponding brightness values are respectively used by luma⁰ _maxAnd luma¹ _maxThe corresponding chromaticity values are respectively indicated by chroma⁰ _maxAnd chroma¹ _maxAnd (4) showing. Further, the mean value calculation is performed on the brightness values corresponding to 2 smaller pixel points, so that the brightness value luma corresponding to the first mean value point can be obtained_minExpressing, mean value calculation is carried out on the brightness values corresponding to 2 larger pixel points, and the brightness value luma corresponding to the second mean value point can be obtained_maxRepresents; similarly, chroma values corresponding to the two average value points can be obtained and used for chroma_minAnd chroma_maxIt is shown, in particular as follows,

luma _min＝(luma ⁰ _min+luma ¹ _min+1)>>1

luma _max＝(luma ⁰ _max+luma ¹ _max+1)>>1

chroma _min＝(chroma ⁰ _min+chroma ¹ _min+1)>>1

chroma _max＝(chroma ⁰ _max+chroma ¹ _max+1)>>1

that is, after obtaining two mean value points (luma)_min，chroma _min) And (luma)_max，chroma _max) Then, the model parameters can be obtained from the two points by a calculation mode of determining a straight line by the two points. Specifically, the model parameters α and β can be calculated by the formula (2)，

Wherein, the model parameter alpha is the slope in the prediction model, and the model parameter beta is the intercept in the prediction model. Thus, after the model parameters are deduced, a prediction model corresponding to the chromaticity component can be obtained according to the model parameters, as shown in formula (1); and then, the prediction model is used for carrying out prediction processing on the chrominance components so as to obtain a prediction value corresponding to the chrominance components.

In another possible implementation manner, for some special cases, such as the boundary condition of the coding block, the unpredictable condition, and the condition that the coding sequence causes that the adjacent reference pixel points cannot be obtained, even the coding block is divided according to tile and slice, at this time, the adjacent areas on the left side, the lower side, the upper side, and the upper right side are not all valid areas, and there may be a case of invalid areas, so that the number of valid pixel points in the first reference pixel set is less than the preset number.

Thus, since the preset number is4, in some embodiments, for S502, when the number of effective pixels in the first reference pixel set is less than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component may include:

and when the number of the effective pixel points in the first reference pixel set is 0 or 2, taking a preset component value as a predicted value corresponding to the to-be-predicted image component.

In some embodiments, for S504, when the number of effective pixels in the second reference pixel set is less than a preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component may include:

and when the number of the effective pixel points in the second reference pixel set is 0 or 2, taking a preset component value as a predicted value corresponding to the to-be-predicted image component.

That is to say, when the preset number is4, no matter the number of the effective pixels in the first reference pixel set is smaller than the preset number, or the number of the effective pixels in the second reference pixel set is smaller than the preset number, at this time, the number of the effective pixels is 0 or 2.

Specifically, when the total number of adjacent reference pixels in the selection area used by the coding block is 0, 0 effective pixels are selected at this time. The following three special cases will result in 0 valid pixel points:

in the first case, for the INTRA _ LT _ CCLM mode, when both the upper neighboring region and the left neighboring region are invalid, the selection region W '═ H' ═ 0 at this time, as shown in fig. 8A; in fig. 8A, a gray diagonal filled region indicates an invalid region;

in the second case, for the INTRA _ L _ CCLM mode, when both the left and lower adjacent regions are invalid, the selection region H' is 0 at this time, as shown in fig. 8B. In fig. 8B, the gray diagonal filled area indicates an invalid area;

in the third case, for the INTRA _ T _ CCLM mode, when both the upper adjacent region and the upper right adjacent region are invalid, the selection region W' is 0 at this time, as shown in fig. 8C. In fig. 8C, a gray diagonal filled area indicates an invalid area.

It should be noted that 0 effective pixel points are determined according to the effectiveness of the adjacent area; that is to say, the number of effective pixels in the first reference pixel set can be determined according to the effectiveness of the adjacent region. When the number of the effective pixels is 0, the model parameter α may be set to 0, and the model parameter β may be set to a preset component value corresponding to the to-be-predicted image component.

Assuming that the image component to be predicted is a chroma component, the predicted values Pred corresponding to the chroma components of all pixel points in the current coding block can be used_C[i,j]All padding is preset component values, namely default values of the chrominance components; in the embodiment of the present application, the default value is a middle value of the chrominance component. Illustratively, assuming that the current video image is an 8-bit video, the corresponding component of the chrominance componentThe range is 0-255, the intermediate value is 128, and the preset component value can be 128; assuming that the current video image is a 10-bit video, the range of the components corresponding to the chrominance components is 0 to 1023, the intermediate value is 512, and the preset component value can be 512.

Specifically, when the total number of adjacent reference pixels in the selection area used by the coding block is 2,2 effective pixels are selected at this time. Still assuming that the size of the coding block is W × H, this will only occur for coding blocks of 2 × N or N × 2. Since the division of the coding blocks of 2 × 2,2 × 4 and 2 × 2 is limited in the VVC latest reference software VTM5.0, that is, in the division of the coding blocks of the video image, the coding blocks of such 3 sizes do not occur; therefore, the value of N is generally such that N.gtoreq.8. The following three special cases will result in 2 valid pixels:

in the first case, for the INTRA _ LT _ CCLM mode, for a coding block of 2 × N or N × 2 (N ≧ 8), when the adjacent region on the side with the side length of 2 is valid and the adjacent region on the side with the side length of N is invalid, the selected region is W '═ 2, H' ═ 0, or W '═ 0, H' ═ 2 at this time, as shown in fig. 9A; in fig. 9A, a gray slant-filled area indicates an invalid area, and a gray solid-filled area indicates an effective area;

in the second case, for the INTRA _ L _ CCLM mode, for an N × 2 coding block (N ≧ 8), when a left side adjacent region with a side length of 2 is valid and a left side adjacent region is invalid, the selected region is H' ═ 2 at this time, as shown in fig. 9B; in fig. 9B, the gray slant-filled area indicates an invalid area, and the gray solid-filled area indicates an effective area;

in the third case, for the INTRA _ T _ CCLM mode, for a coding block of 2 × N (N ≧ 8), when an upper neighboring area with a side length of 2 is valid and an upper right neighboring area is invalid, the selected area is W' ═ 2 at this time, as shown in fig. 9C; in fig. 9C, a gray slant-filled area indicates an invalid area, and a gray solid-filled area indicates an effective area.

It should also be noted that 2 effective pixel points may be determined according to the validity of the adjacent region, may also be determined according to the number of effective pixel points in the selected region, and may also be determined according to other determination conditions, which is not specifically limited in the embodiment of the present application. Therefore, the number of effective pixel points in the first reference pixel set can be determined according to the effectiveness of the adjacent region.

In the solution of the prior art, for the case that the number of effective pixels is 2, 4 pixels are obtained by copying the 2 effective pixels. Exemplarily, assuming that the numbers of the 4 pixel points are 0, 1, 2, and 3, the number 0: selecting a second effective pixel point; number 1: selecting a first effective pixel point; number 2: selecting a second effective pixel point; number 3: selecting a first effective pixel point; and then, determining model parameters alpha and beta according to 4 pixel points with the serial numbers of 0, 1, 2 and 3, so as to establish a prediction model shown as the formula (1), and obtaining a prediction value corresponding to the image component to be predicted through the prediction model.

In the embodiment of the present application, for the case that the number of the effective pixels is 2, no additional "copy" operation is required, and the prediction values corresponding to the to-be-predicted image components are directly filled by using the fixed default values. That is, when the number of effective pixels is 2, the model parameter α may also be set to 0, and the model parameter β may also be set to a preset component value corresponding to the image component to be predicted. Assuming that the image component to be predicted is a chroma component, the predicted values Pred corresponding to the chroma components of all pixel points in the current coding block can be used_C[i,j]All padding is a preset component value, i.e., a default value of the chrominance component.

Thus, in the solution of the prior art, when the number of effective pixels is 2, in order to use the same processing module, an additional "copy" operation needs to be performed at this time to obtain 4 pixels, so that the model parameter can be derived according to the same operation process when the number of effective pixels is4, and an additional "copy" operation is added; moreover, four comparisons and four mean calculations still need to be performed on the obtained 4 pixel points, so that the calculation complexity is high; however, in the embodiment of the present application, the processing when the number of effective pixels is 2 is aligned with the processing when the number of effective pixels is 0, and the same processing module can be directly used without adding additional operations, thereby reducing the computational complexity.

Referring to fig. 10, a schematic flow chart of model parameter derivation provided in the embodiments of the present application is shown. In fig. 10, assuming that a to-be-predicted image component is a chrominance component, first, adjacent reference pixels are obtained from a selection region to form a first adjacent reference pixel set; then judging the number of effective pixel points in the first adjacent reference pixel set; when the number of the effective pixel points is more than or equal to 4, screening the first reference pixel set to obtain a second reference pixel set, and then judging the number of the effective pixel points in the second adjacent reference pixel set; when the number of effective pixel points in the first reference pixel set or the second reference pixel set is 0, setting the model parameter alpha to be 0, setting the model parameter beta to be a default value, and filling a predicted value corresponding to the chrominance component to be the default value at the moment; when the number of the effective pixel points in the first reference pixel set or the second reference pixel set is 2, the processing steps are the same as the processing steps when the number of the effective pixel points is 0; when the number of effective pixel points in the second reference pixel set is4, firstly, two pixel points with larger chrominance components and two pixel points with smaller chrominance components are obtained through 4 times of comparison, and then two average value points are obtained; model parameters alpha and beta are deduced based on the two mean value points, and prediction processing of chromaticity components is carried out according to the constructed prediction model. Therefore, only if the number of effective pixel points in the second reference pixel set meets 4 coding blocks, the derivation of model parameters in the CCLM mode can be executed; and for the coding blocks with the number of effective pixel points less than 4, a default value filling mode is directly adopted, so that the calculation complexity when the number of reference pixel points in the selection area is less than 4 can be reduced, and the coding and decoding performance can be maintained to be basically unchanged.

In the embodiment of the application, the unification of the model parameter derivation process is realized, that is, aiming at the number of effective pixel points used for model parameter derivation in the first reference pixel set, when the number of the effective pixel points in the first reference pixel set is greater than or equal to the preset number, the first reference pixel set is subjected to effective pixel point screening to obtain a second reference pixel set, and then the number of the effective pixel points in the second adjacent reference pixel set is judged; when the number of effective pixel points in the second reference pixel set meets the preset number, the current coding block needs to carry out the steps of deducing model parameters under the CCLM and constructing a prediction model; when the number of effective pixel points in the first reference pixel set or the second reference pixel set is less than the preset number, the current coding block can use a default value to fill a predicted value corresponding to the to-be-predicted image component of the coding block. Therefore, the embodiment of the present application may also provide a simplified process of model parameter derivation, as shown in fig. 11.

The model parameter derivation process shown in fig. 11 is more streamlined than that shown in fig. 10. In fig. 11, assuming that a to-be-predicted image component is a chrominance component and a preset component value is 512, first, an adjacent reference pixel point is obtained from a selection region to form a first adjacent reference pixel set; then judging the number of effective pixel points in the first adjacent reference pixel set; when the number of effective pixel points in the first reference pixel set is larger than or equal to the preset number, screening the first reference pixel set to obtain a second reference pixel set, and then judging the number of effective pixel points in a second adjacent reference pixel set; when the number of effective pixel points in the first reference pixel set or the second reference pixel set is less than the preset number, setting the model parameter alpha to be 0, setting the model parameter beta to be 512, and filling the predicted value corresponding to the chrominance component to be 512 at the moment; when the number of effective pixel points in the second reference pixel set meets the preset number, firstly, obtaining two pixel points with larger chroma component values and two pixel points with smaller chroma component values through 4 times of comparison, and then obtaining two average value points; model parameters alpha and beta are deduced based on the two mean value points, and prediction processing of chromaticity components is carried out according to the constructed prediction model. It should be noted that the derivation of the model parameter in the CCLM mode can be performed only if the number of effective pixels in the second reference pixel set satisfies the preset number of coding blocks; and for the coding blocks with the number of the effective pixel points smaller than the preset number, a default value filling mode is directly adopted, so that the calculation complexity when the number of the reference pixel points in the selection area is less than the preset number can be reduced, and the coding and decoding performance can be maintained to be basically unchanged. Generally, the predetermined number in the embodiment of the present application may be 4.

Further, in this embodiment of the application, the number of effective pixels in the first reference pixel set may be determined according to the number of effective pixels in the selection area. Therefore, the embodiment of the present application may also provide another simplified procedure for model parameter derivation, as shown in fig. 12.

In fig. 12, assuming that a to-be-predicted image component is a chrominance component and a preset component value is 512, a selection area is determined first to obtain a first reference pixel set; then judging the number of effective pixel points in the first reference pixel set; when the number of effective pixel points in the first reference pixel set is larger than or equal to the preset number, screening the first reference pixel set to obtain a second reference pixel set, and then judging the number of effective pixel points in a second adjacent reference pixel set; when the number of effective pixel points in the first reference pixel set or the second reference pixel set is less than the preset number, filling a predicted value corresponding to the chrominance component to 512; when the number of effective pixel points in the second reference pixel set meets the preset number, firstly, obtaining two pixel points with larger chroma component values and two pixel points with smaller chroma component values through 4 times of comparison, and then obtaining two average value points; model parameters alpha and beta are deduced based on the two mean value points, and prediction processing of chromaticity components is carried out according to the constructed prediction model. In this way, the derivation of the model parameters in the CCLM mode can be executed only if the number of effective pixels in the second reference pixel set meets the preset number of coding blocks; and for the coding blocks with the number of the effective pixel points smaller than the preset number, a default value filling mode is directly adopted, so that the calculation complexity when the number of the reference pixel points in the selection area is less than the preset number can be reduced, and the coding and decoding performance can be maintained to be basically unchanged. Generally, the predetermined number in the embodiment of the present application may be 4.

Further, in some embodiments, VVC defines two variables, numSampL and numSampT. Wherein the variable numSampL represents the total number of pixel points in the selection region H'; the variable numSampT represents the total number of pixel points in the selection region W':

for INTRA _ LT _ CCLM mode, nummapt ═ W, nummapl ═ H;

for INTRA _ L _ CCLM mode, numampt ═ 0, numampl ═ min { W + H, H + H };

for INTRA _ T _ CCLM mode, numSampT ═ min { W + H, W + W }, numSampL ═ 0;

in addition, the effectiveness of selecting the region (or the adjacent region) needs to be considered, that is, the variables numSampL and numSampT only represent the number of effective pixels in the above range.

In addition, VVC also defines that when the variables numsamppl and numsampp are both 0 (which will result in that the number of valid pixels that can be screened for model parameter derivation is 0), then directly setting the predicted value corresponding to the chroma component as a default value, otherwise, the derivation of the model parameter needs to be performed, as shown in the following,

if(numSampL＝＝0&&numSampT＝＝0)

setting a predicted value corresponding to the chrominance component as a default value;

else

and deducing the model parameters, and predicting the chrominance component by using the constructed prediction model to obtain a predicted value corresponding to the chrominance component.

However, since the sum of numSampL and numSampT may represent the total number of pixels in the selected region, when numSampL + numSampT is equal to 0, 0 effective pixels are generated; when the numSampL + numSampT is 2,2 effective pixel points are generated, and when the numSampL + numSampT is more than or equal to 4,4 effective pixel points are generated; therefore, the embodiment of the present application can be further expressed as follows (wherein, the preset number can be 4),

if (numSampL + numSampT < predetermined number)

else

The embodiment provides an image component prediction method, which comprises the steps of acquiring a first reference pixel set corresponding to a component to be predicted of a coding block in a video image; when the number of effective pixel points in the first reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component; when the number of effective pixel points in the first reference pixel set is larger than or equal to the preset number, screening the first reference pixel set to obtain a second reference pixel set, wherein the number of effective pixel points in the second reference pixel set is smaller than or equal to the preset number; when the number of effective pixel points in the second reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component; when the number of effective pixel points in the second reference pixel set is equal to the preset number, determining a model parameter through the second reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameter, wherein the prediction model is used for realizing the prediction processing of the image component to be predicted so as to obtain a prediction value corresponding to the image component to be predicted; therefore, on the premise of not changing the encoding and decoding predictive performance, the derivation process of the model parameters is unified, and meanwhile, aiming at the condition that the number of the effective pixel points in the adjacent reference pixel set is less than the preset number, especially the condition that the number of the effective pixel points is 0 or 2, no additional processing module is added, so that no additional processing is needed, and the calculation complexity is reduced.

In another embodiment of the present application, the CCLM mode may be directly disabled when the number of effective pixels in the first reference pixel set is less than the preset number, and a preset component value is used as a predicted value corresponding to the to-be-predicted image component. Therefore, in some embodiments, after the screening the first reference pixel set to obtain the second reference pixel set, the method may further include:

when the number of effective pixel points in the first reference pixel set is smaller than the preset number or the number of effective pixel points in the second reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component;

and when the number of the effective pixel points in the second reference pixel set is greater than or equal to the preset number, adopting a CCLM mode to realize the prediction processing of the image component to be predicted.

It should be noted that, in a case that the number of effective pixels in the first reference pixel set or the second reference pixel set is smaller than the preset number, the CCLM mode may be disabled at this time, for example, an identifier that is used by the CCLM mode is set to "disable the CCLM mode", and at this time, a predicted value corresponding to a to-be-predicted image component is directly filled as a default value; the CCLM mode is only used when the number of effective pixels in the second reference pixel set is greater than or equal to the preset number, for example, the flag indicating whether the CCLM mode is used is set to "enable the CCLM mode", and at this time, the prediction processing on the image component to be predicted can be realized through the CCLM mode.

It should be further noted that, assuming that the image component to be predicted is a chrominance component, and the preset number is4, for all the cases that 2 effective pixels may be generated (where, for the determination manner of generating 2 effective pixels, the embodiment of the present application is not specifically limited), at this time, the model parameter α may also be set to 0, and the model parameter β may be set to an intermediate value (also referred to as a default value) corresponding to the chrominance component, so that the predicted values corresponding to the chrominance components of all the pixels in the coding block may be filled to the default value; in addition, for all cases that may generate 2 valid pixel points, numSampL and numSampT may be set to 0 at this time, so that the prediction values corresponding to the chroma components of all the pixel points in the coding block are filled to default values.

In addition, aiming at all the conditions that 2 effective pixel points are possibly generated, the predicted value corresponding to the chrominance component can be directly filled into a default value; or the CCLM mode can be disabled for all situations where 2 valid pixels may be generated; or for all the cases that 2 or 0 valid pixels may be generated, the CCLM mode may be disabled; or for all cases that may generate 2 or 0 valid pixel points, the prediction value corresponding to the chrominance component may be directly filled as a default value.

Therefore, under the condition that the number of effective pixel points used for model parameter derivation is different, the unification of the model parameter derivation process is realized. Specifically, when the number of effective pixels is 2, the existing processing module is directly called without additional processing (i.e., the processing when the number of effective pixels is 2 is aligned with the processing when the number of effective pixels is 0), so that the computational complexity is also reduced.

In the image component prediction method in the embodiment of the application, based on the latest VVC reference software VTM5.0, under All intra conditions, according to the general test conditions, the average BD-rate changes of a test sequence required by JVET on a Y component, a Cb component and a Cr component are respectively 0.00%, 0.02% and 0.02%, which means that the application has no influence on the coding and decoding performance.

On the premise of not influencing the coding and decoding performance, the method has the following beneficial effects:

first, the method and the device can unify the derivation process of model parameters in the CCLM mode. In the solution of the prior art, for the case that the number of effective pixels is 2, an additional "copy" operation needs to be performed to generate 4 available pixels, so that the same operation as that performed when the number of effective pixels is4 can be performed, and the derivation of the model parameters is completed. However, the method and the device can save extra 'copy' operation, and align the processing when the number of the effective pixels is 2 with the processing when the number of the effective pixels is 0, so that the same processing module can be directly used without adding extra operation, and the unification of the parameter derivation process of the linear model can be realized.

Secondly, the method and the device can also reduce the calculation complexity when the number of the effective pixel points used for model parameter derivation is 2 in the CCLM mode. In the prior art solution, for the case of 2 effective pixels, not only additional "copy" operation is required to generate 4 available pixels, but also the same operation as that for the case of 4 effective pixels, i.e. four comparisons, four averaging calculations, model parameters, is requiredAnd calculating and constructing a prediction model to perform a series of operations such as prediction and the like. However, the present application can save these operations, and directly use the predicted values Pred corresponding to the chrominance components of all the pixels in the current coding block_C[i,j]All padding is a preset component value, i.e., a default value of the chroma component, and does not affect the codec performance.

The embodiment provides an image component prediction method, according to the technical scheme of the embodiment, the number of effective pixels in a first reference pixel set is compared with a preset number, and when the number of effective pixels in the first reference pixel set or a second reference pixel set is smaller than the preset number, a preset default value is directly adopted as a predicted value corresponding to a to-be-predicted image component; when the number of effective pixel points in the second reference pixel set is greater than or equal to the preset number, determining model parameters according to the first reference pixel set to construct a prediction model of the image component to be predicted, so that the derivation process of the model parameters is unified; in addition, aiming at the condition that the number of effective pixel points in the first reference pixel set is smaller than the preset number, because no additional processing module is added, the calculation complexity is reduced.

Based on the same inventive concept of the foregoing embodiment, refer to fig. 13, which shows a schematic structural diagram of an image component prediction apparatus 130 according to an embodiment of the present application. The image component prediction apparatus 130 may include: an acquisition unit 1301, a prediction unit 1302, and a filtering unit 1303, wherein,

the obtaining unit 1301 is configured to obtain a first reference pixel set corresponding to a to-be-predicted image component of a coding block in a video image;

the prediction unit 1302 is configured to, when the number of effective pixels in the first reference pixel set is smaller than a preset number, use a preset component value as a prediction value corresponding to the to-be-predicted image component;

the screening unit 1303 is configured to screen the first reference pixel set to obtain a second reference pixel set when the number of effective pixels in the first reference pixel set is greater than or equal to a preset number; the number of effective pixel points in the second reference pixel set is less than or equal to a preset number;

the prediction unit 1302 is further configured to, when the number of effective pixels in the second reference pixel set is smaller than a preset number, use a preset component value as a prediction value corresponding to the to-be-predicted image component; when the number of effective pixel points in the second reference pixel set is equal to the preset number, determining a model parameter through the second reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameter; the prediction model is used for realizing the prediction processing of the image component to be predicted so as to obtain a prediction value corresponding to the image component to be predicted.

In the above scheme, the obtaining unit 1301 is specifically configured to obtain a reference pixel adjacent to at least one edge of the coding block; wherein the at least one edge comprises a left side of the coding block and/or an upper side of the coding block; and forming a first reference pixel set corresponding to the image component to be predicted based on the reference pixel points.

In the above scheme, the obtaining unit 1301 is specifically configured to obtain a reference pixel point in a reference row or a reference column adjacent to the coding block; wherein the reference row is composed of rows adjacent to the upper side and the upper right side of the coding block, and the reference column is composed of columns adjacent to the left side and the lower left side of the coding block; and forming a first reference pixel set corresponding to the image component to be predicted based on the reference pixel points.

In the foregoing solution, the screening unit 1303 is specifically configured to determine a position of a pixel point to be selected based on a pixel position and/or an image component intensity corresponding to each adjacent reference pixel point in the first reference pixel set; selecting effective pixel points corresponding to the pixel points to be selected from the first reference pixel set according to the determined pixel points to be selected, and forming the selected effective pixel points into a second reference pixel set; and the number of effective pixel points in the second reference pixel set is less than or equal to a preset number.

In the above scheme, referring to fig. 13, the image component predicting apparatus 130 may further include a determining unit 1304 configured to determine a preset component range corresponding to the image component to be predicted based on bit information of the video image; determining a middle value of the preset component range according to the preset component range, and taking the middle value as a predicted value corresponding to the image component to be predicted; wherein the intermediate value is represented as a preset component value.

In the foregoing solution, referring to fig. 13, the image component predicting apparatus 130 may further include a filling unit 1305, configured to perform prediction value filling on the to-be-predicted image component of each pixel by using the preset component value for each pixel in the encoding block.

In the above scheme, the prediction unit 1302 is further configured to perform prediction processing on the to-be-predicted image component of each pixel point in the coding block based on the prediction model, so as to obtain a prediction value corresponding to the to-be-predicted image component of each pixel point.

In the scheme, the value of the preset number is 4; the prediction unit 1302 is further configured to, when the number of effective pixels in the first reference pixel set is 0 or 2, use a preset component value as a prediction value corresponding to the to-be-predicted image component;

correspondingly, the prediction unit 1302 is further configured to, when the number of effective pixels in the second reference pixel set is 0 or 2, use a preset component value as a prediction value corresponding to the to-be-predicted image component.

In the foregoing solution, referring to fig. 13, the image component predicting apparatus 130 may further include a determining unit 1306, configured to use a preset component value as the predicted value corresponding to the to-be-predicted image component when the number of effective pixels in the first reference pixel set is less than a preset number or the number of effective pixels in the second reference pixel set is less than the preset number; and when the number of the effective pixel points in the second reference pixel set is greater than or equal to the preset number, adopting a CCLM mode to realize the prediction processing of the image component to be predicted.

It is understood that in this embodiment, a "unit" may be a part of a circuit, a part of a processor, a part of a program or software, etc., and may also be a module, or may also be non-modular. Moreover, each component in the embodiment may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware or a form of a software functional module.

Based on the understanding that the technical solution of the present embodiment essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, and include several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to execute all or part of the steps of the method of the present embodiment. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

Accordingly, the present embodiments provide a computer storage medium storing an image component prediction program that, when executed by at least one processor, implements the steps of the method of any of the preceding embodiments.

Based on the above-mentioned composition of the image component prediction apparatus 130 and the computer storage medium, referring to fig. 14, which shows a specific hardware structure of the image component prediction apparatus 130 provided in the embodiment of the present application, the specific hardware structure may include: a network interface 1401, a memory 1402, and a processor 1403; the various components are coupled together by a bus system 1404. It is understood that bus system 1404 is used to enable connective communication between these components. The bus system 1404 includes a power bus, a control bus, and a status signal bus in addition to a data bus. The various buses are labeled as bus system 1404 in fig. 14 for the sake of clarity of illustration. The network interface 1401 is used for receiving and sending signals in the process of receiving and sending information with other external network elements;

a memory 1402 for storing a computer program capable of running on the processor 1403;

a processor 1403 for performing, when running the computer program:

It will be appreciated that the memory 1402 in the subject embodiments can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double Data Rate Synchronous Dynamic random access memory (ddr Data Rate SDRAM, ddr SDRAM), Enhanced Synchronous SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 1402 of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.

And processor 1403 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method can be performed by hardware integrated logic circuits or instructions in software form in the processor 1403. The Processor 1403 may be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 1402, and the processor 1403 reads the information in the memory 1402 and completes the steps of the above method in combination with the hardware thereof.

It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the Processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units configured to perform the functions described herein, or a combination thereof.

For a software implementation, the techniques described herein may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.

Optionally, as another embodiment, the processor 1403 is further configured to, when running the computer program, perform the steps of the method of any of the previous embodiments.

Referring to fig. 15, a schematic diagram of a constituent structure of an encoder according to an embodiment of the present application is shown. As shown in fig. 15, the encoder 150 may include at least the image component prediction apparatus 130 described in any of the previous embodiments.

Referring to fig. 16, a schematic diagram of a component structure of a decoder according to an embodiment of the present application is shown. As shown in fig. 16, the decoder 160 may include at least the image component prediction apparatus 130 described in any of the previous embodiments.

It should be noted that, in the present application, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.

The methods disclosed in the several method embodiments provided in the present application may be combined arbitrarily without conflict to obtain new method embodiments.

Features disclosed in several of the product embodiments provided in the present application may be combined in any combination to yield new product embodiments without conflict.

The features disclosed in the several method or apparatus embodiments provided in the present application may be combined arbitrarily, without conflict, to arrive at new method embodiments or apparatus embodiments.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Industrial applicability

In the embodiment of the application, a first reference pixel set corresponding to a component of a to-be-predicted image of a coding block in a video image is obtained; when the number of effective pixel points in the first reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the image component to be predicted; when the number of effective pixel points in the first reference pixel set is larger than or equal to the preset number, screening the first reference pixel set to obtain a second reference pixel set, wherein the number of effective pixel points in the second reference pixel set is smaller than or equal to the preset number; when the number of effective pixel points in the second reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the image component to be predicted; when the number of effective pixel points in the second reference pixel set is equal to the preset number, determining a model parameter through the second reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameter, wherein the prediction model is used for realizing the prediction processing of the image component to be predicted so as to obtain a prediction value corresponding to the image component to be predicted; in this way, when the number of effective pixels in the first reference pixel set is smaller than the preset number or the number of effective pixels in the second reference pixel set is smaller than the preset number, the preset default value is directly adopted as the predicted value corresponding to the image component to be predicted; only when the number of effective pixel points in the second reference pixel set meets the preset number, determining model parameters according to the first reference pixel set to establish a prediction model of the image component to be predicted, so that the derivation process of the model parameters is unified; in addition, for the condition that the number of effective pixels in the first reference pixel set or the second reference pixel set is smaller than the preset number, especially for the condition that the number of effective pixels is 0 or 2, because no additional processing module is added, the preset default value is directly adopted as the predicted value corresponding to the image component to be predicted, so that no additional processing is needed, and the calculation complexity is reduced.

Claims

A method of image component prediction, the method comprising:

acquiring a first reference pixel set corresponding to a component of a to-be-predicted image of a coding block in a video image;

when the number of effective pixel points in the first reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component;

when the number of effective pixel points in the first reference pixel set is greater than or equal to a preset number, screening the first reference pixel set to obtain a second reference pixel set; the number of effective pixel points in the second reference pixel set is less than or equal to a preset number;

when the number of effective pixel points in the second reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component;

when the number of effective pixel points in the second reference pixel set is equal to the preset number, determining a model parameter through the second reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameter; the prediction model is used for realizing the prediction processing of the image component to be predicted so as to obtain a prediction value corresponding to the image component to be predicted.
The method of claim 1, wherein said obtaining a first set of reference pixels corresponding to image components to be predicted for a coded block in a video image comprises:

acquiring a reference pixel point adjacent to at least one edge of the coding block; wherein the at least one edge comprises a left side of the coding block and/or an upper side of the coding block;

and forming a first reference pixel set corresponding to the image component to be predicted based on the reference pixel points.
The method of claim 1, wherein said obtaining a first set of reference pixels corresponding to image components to be predicted for a coded block in a video image comprises:

acquiring reference pixel points in reference rows or reference columns adjacent to the coding blocks; wherein the reference row is composed of rows adjacent to the upper side and the upper right side of the coding block, and the reference column is composed of columns adjacent to the left side and the lower left side of the coding block;

and forming a first reference pixel set corresponding to the image component to be predicted based on the reference pixel points.
The method according to any one of claims 1 to 3, wherein the screening the first set of reference pixels to obtain a second set of reference pixels comprises:

determining the position of a pixel point to be selected based on the pixel position and/or the image component intensity corresponding to each adjacent reference pixel point in the first reference pixel set;

selecting effective pixel points corresponding to the pixel points to be selected from the first reference pixel set according to the determined pixel points to be selected, and forming the selected effective pixel points into a second reference pixel set; and the number of effective pixel points in the second reference pixel set is less than or equal to a preset number.
The method according to claim 1, wherein when the number of effective pixels in the first reference pixel set is less than a preset number or the number of effective pixels in the second reference pixel set is less than a preset number, the using a preset component value as the predicted value corresponding to the to-be-predicted image component comprises:

determining a preset component range corresponding to the image component to be predicted based on the bit information of the video image;

determining a middle value of the preset component range according to the preset component range, and taking the middle value as a predicted value corresponding to the image component to be predicted; wherein the intermediate value is represented as a preset component value.
The method according to claim 1, wherein after said taking a preset component value as a predicted value corresponding to said image component to be predicted, said method further comprises:

and aiming at each pixel point in the coding block, filling a predicted value of the component of the image to be predicted of each pixel point by using the preset component value.
The method according to claim 1, wherein after the obtaining of the prediction model corresponding to the image component to be predicted according to the model parameter, the method further comprises:

and performing prediction processing on the component of the image to be predicted of each pixel point in the coding block based on the prediction model to obtain a prediction value corresponding to the component of the image to be predicted of each pixel point.
The method of claim 1, wherein the predetermined number takes the value of 4; when the number of effective pixels in the first reference pixel set is less than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component, including:

when the number of effective pixel points in the first reference pixel set is 0 or 2, taking a preset component value as a predicted value corresponding to the to-be-predicted image component;

correspondingly, when the number of effective pixels in the second reference pixel set is less than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component, includes:

and when the number of the effective pixel points in the second reference pixel set is 0 or 2, taking a preset component value as a predicted value corresponding to the to-be-predicted image component.
The method of claim 1, wherein after the filtering the first set of reference pixels to obtain a second set of reference pixels, the method further comprises:

when the number of effective pixel points in the first reference pixel set is smaller than the preset number or the number of effective pixel points in the second reference pixel set is smaller than the preset number, taking a preset component value as a predicted value corresponding to the to-be-predicted image component;

and when the number of the effective pixel points in the second reference pixel set is greater than or equal to the preset number, adopting a CCLM mode to realize the prediction processing of the image component to be predicted.
An image component prediction device, the image component prediction device comprising: an acquisition unit, a prediction unit, and a screening unit, wherein,

the acquiring unit is configured to acquire a first reference pixel set corresponding to a to-be-predicted image component of a coding block in a video image;

the prediction unit is configured to, when the number of effective pixels in the first reference pixel set is smaller than a preset number, use a preset component value as a prediction value corresponding to the to-be-predicted image component;

the screening unit is configured to screen the first reference pixel set to obtain a second reference pixel set when the number of effective pixels in the first reference pixel set is greater than or equal to a preset number; the number of effective pixel points in the second reference pixel set is less than or equal to a preset number;

the prediction unit is further configured to, when the number of effective pixels in the second reference pixel set is smaller than a preset number, use a preset component value as a prediction value corresponding to the to-be-predicted image component; when the number of effective pixel points in the second reference pixel set is equal to the preset number, determining a model parameter through the second reference pixel set, and obtaining a prediction model corresponding to the image component to be predicted according to the model parameter; the prediction model is used for realizing the prediction processing of the image component to be predicted so as to obtain a prediction value corresponding to the image component to be predicted.
An image component prediction apparatus, wherein the image component prediction apparatus comprises: a memory and a processor;

the memory for storing a computer program operable on the processor;

the processor, when running the computer program, is configured to perform the method of any of claims 1 to 9.
A computer storage medium, wherein the computer storage medium stores an image component prediction program that, when executed by at least one processor, implements the method of any of claims 1-9.